Skip to main content

Optional background reading

Introduction to Markov Processes, 2019/20, Semester 2
Dr Matthew Aldridge
Tutor information is taken from the Module Catalogue

It should be possible to do well on this module by attending the lectures and workshops, plus working on the problem sheets, assignments and practicals, without any further reading. However, for students who would like some book recommendations for wider reading or an alternative view on the material, I recommend the following.

The two books I found most useful in planning the course were:• J.R. Norris, Markov Chains ISBN: 0521481813 (pbk), Cambridge Series in Statistical and Probabilistic Mathematics, Cambridge University Press, 1997. Chapters 1-3.

• G.R. Grimmett and D.R. Stirzaker, Probability and Random Processes, 3rd edition, Oxford University Press, 2001. Chapter 6.
Norris discusses only Markov processes, and has some more detailed material that goes beyond this module. Grimmet and Stirzaker is an excellent handbook that covers all of undergraduate probability. Extract available as an Online Course Reading in Minerva.

The approach of Grimmet and Stirzaker is very closely mirrored in
• G. Grimmet and D. Walsh, Probability : an introduction ISBN: 0198532644 (pbk ; cased) : £9.95; 0198532725, 2nd edition, Oxford University Press, 2014. Chapter 12.
which be useful if you have a copy to hand, or if the library runs out of Grimmet and Stirzaker.

A gentler introduction with plenty of examples is provided by
• P.W. Jones and P. Smith, Stochastic Processes: an introduction, 3nd edition, Texts in Statistical Science, CRC Press, 2018. Chapters 2-7.  
although it doesn't cover everything in this module. It's available online from the University library.

Finally, I've heard good things about
• D.R. Stirzaker, Elementary Probability, 2nd edition, Cambridge University Press, 2003. Chapter 9.
although I haven't used it myself. It's also available online.

This list was last updated on 25/01/2019